Results 11 to 20 of about 118,514 (262)
Direct Reduction of Bias of the Classical Hill Estimator
Revstat Statistical Journal, 2005 In this paper we are interested in an adequate estimation of the dominant component of the bias of Hill’s estimator of a positive tail index γ, in order to remove it from the classical Hill estimator in different asymptotically equivalent ways.
Frederico Caeiro +2 more
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Minimum-Variance Reduced-Bias Tail Index and High Quantile Estimation
Revstat Statistical Journal, 2008 Heavy tailed-models are quite useful in many fields, like insurance, finance, telecommunications, internet traffic, among others, and it is often necessary to estimate a high quantile, i.e., a value that is exceeded with a probability p, small.
Frederico Caeiro , M. Ivette Gomes
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Arab Journal of Mathematical Sciences, 2017 The problem of estimating the mean function of a compound cyclic Poisson process with linear trend is considered. An estimator of this mean function is constructed and investigated.
Bonno Andri Wibowo +2 more
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Variance based weighting of multisensory head rotation signals for verticality perception.
PLoS ONE, 2020 We tested the hypothesis that the brain uses a variance-based weighting of multisensory cues to estimate head rotation to perceive which way is up.
Christopher J Dakin +4 more
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Modern Stochastics: Theory and Applications, 2021 In this study, we consider a bias reduction of the conditional maximum likelihood estimators for the unknown parameters of a Gaussian second-order moving average (MA(2)) model.
Fumiaki Honda, Takeshi Kurosawa
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Nonparametric Estimation of ROC Surfaces Under Verification Bias
Revstat Statistical Journal, 2020 Verification bias is a well known problem that can affect the statistical evaluation of the predictive ability of a diagnostic test when the true disease status is unknown for some of the patients under study.
Khanh To Duc +2 more
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Asymptotic properties of the Bernstein density copula for dependent data [PDF]
, 2008 Copulas are extensively used for dependence modeling. In many cases the data does not reveal how the dependence can be modeled using a particular parametric copula. Nonparametric copulas do not share this problem since they are entirely data based.
BOUEZMARNI, Taoufik +2 more
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A Study of Seven Asymmetric Kernels for the Estimation of Cumulative Distribution Functions
Mathematics, 2021 In this paper, we complement a study recently conducted in a paper of H.A. Mombeni, B. Masouri and M.R. Akhoond by introducing five new asymmetric kernel c.d.f.
Pierre Lafaye de Micheaux +1 more
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Desimal, 2020 In this article, we provided a numerical simulation for asymptotic normality of a kernel type estimator for the intensity obtained as a product of a periodic function with the power trend function of a nonhomogeneous Poisson Process.
Ikhsan Maulidi +2 more
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Estimation of a Finite Population Mean under Random Nonresponse Using Kernel Weights
Journal of Probability and Statistics, 2020 Nonresponse is a potential source of errors in sample surveys. It introduces bias and large variance in the estimation of finite population parameters. Regression models have been recognized as one of the techniques of reducing bias and variance due to ...
Nelson Kiprono Bii +2 more
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